Codebase Onboarding

SkillAI & models

Once added, your AI can study a codebase and turn it into clear onboarding documentation for engineers, tech leads, and contractors. It gathers the important facts quickly and produces the same kind of write-up each time, so new team members can get up to speed on unfamiliar projects.

Available today. Use it from your connected AI after setup.

No other account needed.

Point your AI at the codebase you want documented and ask for an onboarding guide, an architecture overview, or a tech-lead briefing. Reuse the same request for each new project or person joining the team.

Then ask your AI: use the Codebase Onboarding skill

What your AI can do with it

Analyze an unfamiliar codebase and gather the key facts
Generate onboarding documentation for new engineers
Write architecture-overview docs for a new project
Produce tech-lead briefings for unfamiliar repositories
Create onboarding materials for contractors joining a project
Repeat the same onboarding output across projects and new hires

What this skill tells your AI

The instructions your AI receives, as published by alirezarezvani/claude-skills in .gemini/skills/codebase-onboarding/SKILL.md and read by ahel’s review.

Tier: POWERFUL Category: Engineering Domain: Documentation / Developer Experience

Overview

Analyze a codebase and generate onboarding documentation for engineers, tech leads, and contractors. This skill is optimized for fast fact-gathering and repeatable onboarding outputs.

Core Capabilities

Architecture and stack discovery from repository signals
Key file and config inventory for new contributors
Local setup and common-task guidance generation
Audience-aware documentation framing
Debugging and contribution checklist scaffolding

When to Use

Onboarding a new team member or contractor
Rebuilding stale project docs after large refactors
Preparing internal handoff documentation
Creating a standardized onboarding packet for services

Quick Start

# 1) Gather codebase facts
python3 scripts/codebase_analyzer.py /path/to/repo

# 2) Export machine-readable output
python3 scripts/codebase_analyzer.py /path/to/repo --json

# 3) Use the template to draft onboarding docs
# See references/onboarding-template.md

Recommended Workflow

Run scripts/codebase_analyzer.py against the target repository.
Capture key signals: file counts, detected languages, config files, top-level structure.
Fill the onboarding template in references/onboarding-template.md.
Tailor output depth by audience:
- Junior: setup + guardrails
- Senior: architecture + operational concerns
- Contractor: scoped ownership + integration boundaries